A search engine is an information retrieval system designed to find information stored on a computer system, such as on the World Wide Web or inside a corporate or proprietary network. The search engine allows a user to search for content meeting specific criteria (e.g., typically containing a given word or phrase) and retrieves a list of items that match the criteria. This list is often sorted with respect to some measure of relevance of the results.
Major search engines rarely focus on a single data type, though. For example, Internet search engines offer searches for Web pages, as well as the ability to search for images, groups, news, shopping, videos, people, and many other categories. These different categories of information are referred to as “collections.” Frequently, the control offered to the user to specify what collection to search is a listing of links or tabs provided near the text field for entering text searchable words.
By providing the ability to search a host of collections, the user is empowered to locate a greater body of information from a single site. However, the common implementation selecting which collection to search has its shortcomings. For example, at times, the user may forget what collection they are currently searching, and fail to find the target materials, as they are stored in another collection. Illustratively, it is not uncommon that a user wanting to find an article struggles with the task because the user was searching a “book” collection rather than an “article” collection. Other times, the user might believe which collection to search, but the answer is stored in another collection.
Also, when seeking an abstract piece of information, it may not be evident which collection the user needs to search. For example, a user may want to know the status of a tax law that was being debated by the U.S. Congress. The user might search the World Wide Web and find a page on tax law that has not been updated and, as such, the user may wrongly conclude that the law had not passed. Yet, if the user searched “Video” or “Audio” collections, the user may have found a broadcast that indicates the law did pass, or if they had searched the “News” collection they may have found an article describing the passing of the law.
Search engines have been grappling with such problems for a long time. One solution proposed is to allow the user to select searchable collections in order to obtain a full listing of all results for each collection. However, there is pressure on the user to decide what collection(s) they need to search. Furthermore, this can lead to the opposite problem: an overload of results that the critical result gets lost in the voluminous search results.
Another solution is to provide reminders to the user in the search results area. This solution does provide the user with a reminder that the information they need may be found in one of the collections not searched. But there are a number of limitations/problems with this solution. For example, the system is almost behaving as if the results from the other collection are more important than the collection the user opted to search. That is, the user's primary search results are pushed down in favor of supplying results from a collection the user did not specifically search (e.g., News).
Accordingly, there exists a need in the art to overcome the deficiencies and limitations described hereinabove.